PREDICTING HIGHEST PROFESSIONAL QUALIFICATION APPLYING THE USAGE OF STRATEGIC MANAGEMENT TOOLS AND TECHNIQUES AND YEARS OF PROFESSIONAL EXPERIENCE
Keywords:
adaptive boosting, data mining, machine learning, professional practice, property valuation, real estate appraisal, strategic management, strategyDOI:
https://doi.org/10.17654/0972361723001Abstract
Professional service firms employ strategic management (SM) in achieving their long term goals. Estate valuation and surveying firms, a subset of professional firms, are not an outlier in SM practices and strategic management tools and techniques (SMTT) usage. The aim of this paper is to predict the highest professional qualification of Estate Surveyors and Valuers (ESVs) in Southwest Nigeria, applying the degree of usage of strategic management tools and techniques (SMTTs) and years of professional experience. In this context, the highest professional qualification is being a Fellow of the Nigerian Institution of Estate Surveyors and Valuers (FNIESV), a step above being an Associate (ANIESV). The data is from a field survey and data mining models were used. The result showed that professional status (FNIESV or ANIESV) could be classified based on SMTT usage and years of professional experience. Adaptive boosting gave the best classification accuracy, specificity, and other evolution metrics.
Received: August 13, 2022; Accepted: October 12, 2022; Published: December 16, 2022
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